The present invention relates to atrial fibrillation and, more particularly, to a hybrid model and diagnostic process for atrial fibrillation.
Atrial fibrillation (AFib) is a type of arrhythmia, where atria contract fast and/or irregularly due to a dysfunctional cardiac electrical system. AFib starts paroxysmally, and advances to a persistent/permanent stage. Early diagnosis and treatment in the paroxysmal stage, reduces chances of stroke. However, AFib usually remains undiagnosed until the disease progresses.
Current methods of diagnosing AFib are based on symptoms, such as palpitation and dizziness, after which an electrocardiogram (ECG) may be taken to check for AFib. However, the ECG pattern corresponding to AFib will occur only when the patient is experiencing an episode of AFib, which may not necessarily happen during the ECG recording, since AFib starts out initially as paroxysmal (rare occurrences). Thus AFib can remain undiagnosed till the disease progresses and episodes are more persistent, which by that time can increase the risk of stroke.
Long term ECG recording devices such as Holter or Event monitors are time consuming and do not give results in real time. The Echocardiography method is noninvasive, but requires special equipment. Also none of the techniques are for early diagnosis of the disease.
As can be seen, there is a need for an improved diagnostic process for atrial fibrillation.